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arXiv 2103.08554astro-ph.CO
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计算星系团射电晕通量密度的稳健模型:Halo-FDCA

A Robust Model for Flux Density Calculations of Radio Halos in Galaxy Clusters: Halo-FDCA

J. M. Boxelaar, R. J. van Weeren, A. Botteon

摘要:

在这里,我们提出了Halo-FDCA,一个强大的开源Python软件包,用于建模和估计星系团中无线电(迷你)晕的总通量密度。射电晕是在星系团中发现的扩展(大小约为200 - 1500千秒差距)同步辐射源,可以追踪团内介质(ICM)中宇宙射线和磁场的存在。这些光源位于中心位置,表面亮度较低。它们的确切起源仍然未知,但它们可能与合并或晃动驱动的ICM湍流在原位重新加速的宇宙射线有关。所提出的算法结合了数值功率的马尔可夫链蒙特卡罗例程和多个理论模型来估计从无线电图像和其相关的不确定性的无线电晕的总无线电通量密度。该方法引入了一种灵活的分析拟合过程,以取代现有的简单的手动测量容易产生偏差和不准确。它可以很容易地确定发射的属性,特别适合于未来的研究大样本的集群。

英文摘要:

Here we present Halo-FDCA, a robust open source Python package for modeling and estimating total flux densities of radio (mini) halos in galaxy clusters. Radio halos are extended ( ~200 - 1500 kpc in size) synchrotron emitting sources found in galaxy clusters that trace the presence of cosmic rays and magnetic fields in the intracluster medium (ICM). These sources are centrally located and have a low surface brightness. Their exact origin is still unknown but they are likely related to cosmic rays being re-accelerated in-situ by merger or sloshing driven ICM turbulence. The presented algorithm combines the numerical power of the Markov Chain Monte Carlo routine and multiple theoretical models to estimate the total radio flux density of a radio halo from a radio image and its associated uncertainty. This method introduces a flexible analytic fitting procedure to replace existing simplistic manual measurements prone to biases and inaccuracies. It allows to easily determine the properties of the emission and is particularly suitable for future studies of large samples of clusters.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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